





"""simple docstring"""






from PIL import Image

def      __A   (      a_    :Image)		->		Image:
				__a							,    __a			:    Tuple      							=	image.size
				__a			:    Optional[Any]      							=	0
				__a			:    Dict      							=	image.load()
				for i in range(a_):
								for j in range(a_):
												__a			:    Optional[Any]      							=	pixels[j, i]
												mean += pixel
				mean //= width * height

				for j in range(a_):
								for i in range(a_):
												__a			:    Optional[Any]      							=	2_55 if pixels[i, j] > mean else 0
				return image


if __name__ == "__main__":
		A			      =	mean_threshold(Image.open('''path_to_image''').convert('''L'''))
		image.save('''output_image_path''')



'''simple docstring'''


import subprocess
import sys

from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch





class        lowercase__    (		_snake_case   ):





							'''simple docstring'''


							@require_torch
							def UpperCAmelCase_      (       self    ):
											# this test is a bit tricky since TRANSFORMERS_OFFLINE can only be changed before
											# `transformers` is loaded, and it's too late for inside pytest - so we are changing it
											# while running an external program

											# python one-liner segments

											# this must be loaded before socket.socket is monkey-patched
											_SCREAMING_SNAKE_CASE					:			Optional[int]							= """
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
        """

											_SCREAMING_SNAKE_CASE					:			Dict							= """
mname = \"hf-internal-testing/tiny-random-bert\"
BertConfig.from_pretrained(mname)
BertModel.from_pretrained(mname)
BertTokenizer.from_pretrained(mname)
pipe = pipeline(task=\"fill-mask\", model=mname)
print(\"success\")
        """

											_SCREAMING_SNAKE_CASE					:			Optional[Any]							= """
import socket
def offline_socket(*args, **kwargs): raise RuntimeError(\"Offline mode is enabled, we shouldn't access internet\")
socket.socket = offline_socket
        """

											# Force fetching the files so that we can use the cache
											_SCREAMING_SNAKE_CASE					:			Optional[Any]							= """hf-internal-testing/tiny-random-bert"""
											BertConfig.from_pretrained(__snake_case    )
											BertModel.from_pretrained(__snake_case    )
											BertTokenizer.from_pretrained(__snake_case    )
											pipeline(task="""fill-mask"""       ,   model=__snake_case    )

											# baseline - just load from_pretrained with normal network
											_SCREAMING_SNAKE_CASE					:			Union[str, Any]							= [sys.executable, """-c""", """\n""".join([load, run, mock]    )]

											# should succeed
											_SCREAMING_SNAKE_CASE					:			Optional[Any]							= self.get_env()
											# should succeed as TRANSFORMERS_OFFLINE=1 tells it to use local files
											_SCREAMING_SNAKE_CASE					:			int							= """1"""
											_SCREAMING_SNAKE_CASE					:			str							= subprocess.run(__snake_case       ,   env=__snake_case       ,   check=__snake_case       ,   capture_output=__snake_case    )
											self.assertEqual(result.returncode       ,   0       ,   result.stderr    )
											self.assertIn("""success"""       ,   result.stdout.decode()    )






							@require_torch
							def UpperCAmelCase_      (       self    ):
											# python one-liner segments
											# this must be loaded before socket.socket is monkey-patched
											_SCREAMING_SNAKE_CASE					:			Optional[int]							= """
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
        """

											_SCREAMING_SNAKE_CASE					:			Any							= """
mname = \"hf-internal-testing/tiny-random-bert\"
BertConfig.from_pretrained(mname)
BertModel.from_pretrained(mname)
BertTokenizer.from_pretrained(mname)
pipe = pipeline(task=\"fill-mask\", model=mname)
print(\"success\")
        """

											_SCREAMING_SNAKE_CASE					:			List[Any]							= """
import socket
def offline_socket(*args, **kwargs): raise socket.error(\"Faking flaky internet\")
socket.socket = offline_socket
        """

											# Force fetching the files so that we can use the cache
											_SCREAMING_SNAKE_CASE					:			Tuple							= """hf-internal-testing/tiny-random-bert"""
											BertConfig.from_pretrained(__snake_case    )
											BertModel.from_pretrained(__snake_case    )
											BertTokenizer.from_pretrained(__snake_case    )
											pipeline(task="""fill-mask"""       ,   model=__snake_case    )

											# baseline - just load from_pretrained with normal network
											_SCREAMING_SNAKE_CASE					:			Tuple							= [sys.executable, """-c""", """\n""".join([load, run, mock]    )]

											# should succeed
											_SCREAMING_SNAKE_CASE					:			str							= self.get_env()
											_SCREAMING_SNAKE_CASE					:			Tuple							= subprocess.run(__snake_case       ,   env=__snake_case       ,   check=__snake_case       ,   capture_output=__snake_case    )
											self.assertEqual(result.returncode       ,   0       ,   result.stderr    )
											self.assertIn("""success"""       ,   result.stdout.decode()    )






							@require_torch
							def UpperCAmelCase_      (       self    ):
											# this test is a bit tricky since TRANSFORMERS_OFFLINE can only be changed before
											# `transformers` is loaded, and it's too late for inside pytest - so we are changing it
											# while running an external program

											# python one-liner segments

											# this must be loaded before socket.socket is monkey-patched
											_SCREAMING_SNAKE_CASE					:			Tuple							= """
from transformers import BertConfig, BertModel, BertTokenizer
        """

											_SCREAMING_SNAKE_CASE					:			str							= """
mname = \"hf-internal-testing/tiny-random-bert-sharded\"
BertConfig.from_pretrained(mname)
BertModel.from_pretrained(mname)
print(\"success\")
        """

											_SCREAMING_SNAKE_CASE					:			List[Any]							= """
import socket
def offline_socket(*args, **kwargs): raise ValueError(\"Offline mode is enabled\")
socket.socket = offline_socket
        """

											# baseline - just load from_pretrained with normal network
											_SCREAMING_SNAKE_CASE					:			List[str]							= [sys.executable, """-c""", """\n""".join([load, run]    )]

											# should succeed
											_SCREAMING_SNAKE_CASE					:			List[str]							= self.get_env()
											_SCREAMING_SNAKE_CASE					:			Optional[Any]							= subprocess.run(__snake_case       ,   env=__snake_case       ,   check=__snake_case       ,   capture_output=__snake_case    )
											self.assertEqual(result.returncode       ,   0       ,   result.stderr    )
											self.assertIn("""success"""       ,   result.stdout.decode()    )

											# next emulate no network
											_SCREAMING_SNAKE_CASE					:			List[str]							= [sys.executable, """-c""", """\n""".join([load, mock, run]    )]

											# Doesn't fail anymore since the model is in the cache due to other tests, so commenting this.
											# env["TRANSFORMERS_OFFLINE"] = "0"
											# result = subprocess.run(cmd, env=env, check=False, capture_output=True)
											# self.assertEqual(result.returncode, 1, result.stderr)

											# should succeed as TRANSFORMERS_OFFLINE=1 tells it to use local files
											_SCREAMING_SNAKE_CASE					:			Dict							= """1"""
											_SCREAMING_SNAKE_CASE					:			int							= subprocess.run(__snake_case       ,   env=__snake_case       ,   check=__snake_case       ,   capture_output=__snake_case    )
											self.assertEqual(result.returncode       ,   0       ,   result.stderr    )
											self.assertIn("""success"""       ,   result.stdout.decode()    )






							@require_torch
							def UpperCAmelCase_      (       self    ):
											_SCREAMING_SNAKE_CASE					:			Optional[int]							= """
from transformers import pipeline
        """
											_SCREAMING_SNAKE_CASE					:			int							= """
mname = \"hf-internal-testing/tiny-random-bert\"
pipe = pipeline(model=mname)
        """

											_SCREAMING_SNAKE_CASE					:			Any							= """
import socket
def offline_socket(*args, **kwargs): raise socket.error(\"Offline mode is enabled\")
socket.socket = offline_socket
        """
											_SCREAMING_SNAKE_CASE					:			Dict							= self.get_env()
											_SCREAMING_SNAKE_CASE					:			Any							= """1"""
											_SCREAMING_SNAKE_CASE					:			str							= [sys.executable, """-c""", """\n""".join([load, mock, run]    )]
											_SCREAMING_SNAKE_CASE					:			List[Any]							= subprocess.run(__snake_case       ,   env=__snake_case       ,   check=__snake_case       ,   capture_output=__snake_case    )
											self.assertEqual(result.returncode       ,   1       ,   result.stderr    )
											self.assertIn(
											    """You cannot infer task automatically within `pipeline` when using offline mode"""       ,   result.stderr.decode().replace("""\n"""       ,   """"""    )       ,   )






							@require_torch
							def UpperCAmelCase_      (       self    ):
											_SCREAMING_SNAKE_CASE					:			Optional[int]							= """
from transformers import AutoModel
        """
											_SCREAMING_SNAKE_CASE					:			Tuple							= """
mname = \"hf-internal-testing/test_dynamic_model\"
AutoModel.from_pretrained(mname, trust_remote_code=True)
print(\"success\")
        """

											# baseline - just load from_pretrained with normal network
											_SCREAMING_SNAKE_CASE					:			List[str]							= [sys.executable, """-c""", """\n""".join([load, run]    )]

											# should succeed
											_SCREAMING_SNAKE_CASE					:			Optional[Any]							= self.get_env()
											_SCREAMING_SNAKE_CASE					:			List[str]							= subprocess.run(__snake_case       ,   env=__snake_case       ,   check=__snake_case       ,   capture_output=__snake_case    )
											self.assertEqual(result.returncode       ,   0       ,   result.stderr    )
											self.assertIn("""success"""       ,   result.stdout.decode()    )

											# should succeed as TRANSFORMERS_OFFLINE=1 tells it to use local files
											_SCREAMING_SNAKE_CASE					:			Optional[Any]							= """1"""
											_SCREAMING_SNAKE_CASE					:			Any							= subprocess.run(__snake_case       ,   env=__snake_case       ,   check=__snake_case       ,   capture_output=__snake_case    )
											self.assertEqual(result.returncode       ,   0       ,   result.stderr    )
											self.assertIn("""success"""       ,   result.stdout.decode()    )




